• Title/Summary/Keyword: two-dimensional detection

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Anti-Spoofing Method Using Double Peak Detection in the Two-Dimensional C/A Code Search Space (이차원 C/A 코드 검색 공간에서의 이중피크 검출을 이용한 기만신호 대응 기법)

  • Kwon, Keum-Cheol;Yang, Cheol-Kwan;Shim, Duk-Sun
    • Journal of Advanced Navigation Technology
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    • v.17 no.2
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    • pp.157-164
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    • 2013
  • In the presence of spoofing signal the GPS signal having the same PRN with the spoofer is hard to be acquired since the power of spoofing signal is usually stronger than that of GPS signal. If a spoofing signal exists for the same PRN, there are double peaks in two-dimensional space of frequency and code phase in acquisition stage. Using double peak information it is possible to detect spoofing signal and acquire GPS information through separate channel tracking. In this paper we introduce an anti-spoofing method using double peak detection, and thus can acquire GPS navigation data after two-channel tracking for the same PRN as the spoofing signal.

Robust Optical Flow Detection Using 2D histogram with Variable Resolution (가변 분해능을 가진 2차원 히스토그램을 이용한 강건한 광류인식)

  • CHON Jaechoon;KIM Hyongsuk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.51-64
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    • 2005
  • The proposed algorithm is to achieve the robust optical flow detection which is applicable for the case that the outlier rate is over $80\%$. If the outlier rate of optical flows is over $30\%$, the discrimination between the inliers and outlier with the conventional algorithm is very difficult. The proposed algorithm is to overcome such difficulty withthree steps of grouping algorithm; 1) constructing the 2 D histogram with two axies of the lengths and the directions of optical flows. 2) sorting the number of optical flows in each bin of the two-dimensional histogram in the descendingorder and removing some bins with lower number of optical flows than threshold 3) increasing the resolution of the two-dimensional histogram if the number of optical flows in a specific bin is over $20\%$ and decreasing theresolution if the number of optical flows is less than $10\%$. Such processing is repeated until the the number of optical flows falls into the range of $10\%-20\%$ in all the bins. The proposed algorithm works well on the different kinds of images with many of wrong optical flows. Experimental results are included.

Detection Method for Bean Cotyledon Locations under Vinyl Mulch Using Multiple Infrared Sensors

  • Lee, Kyou-Seung;Cho, Yong-jin;Lee, Dong-Hoon
    • Journal of Biosystems Engineering
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    • v.41 no.3
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    • pp.263-272
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    • 2016
  • Purpose: Pulse crop damage due to wild birds is a serious problem, to the extent that the rate of damage during the period of time between seeding and the stage of cotyledon reaches 45.4% on average. This study investigated a method of fundamentally blocking birds from eating crops by conducting vinyl mulching after seeding and identifying the growing locations for beans to perform punching. Methods: Infrared (IR) sensors that could measure the temperature without contact were used to recognize the locations of soybean cotyledons below vinyl mulch. To expand the measurable range, 10 IR sensors were arranged in a linear array. A sliding mechanical device was used to reconstruct the two-dimensional spatial variance information of targets. Spatial interpolation was applied to the two-dimensional temperature distribution information measured in real time to improve the resolution of the bean coleoptile locations. The temperature distributions above the vinyl mulch for five species of soybeans over a period of six days from the appearance of the cotyledon stage were analyzed. Results: During the experimental period, cases where bean cotyledons did and did not come into contact with the bottom of the vinyl mulch were both observed, and depended on the degree of growth of the bean cotyledons. Although the locations of bean cotyledons could be estimated through temperature distribution analyses in cases where they came into contact with the bottom of the vinyl mulch, this estimation showed somewhat large errors according to the time that had passed after the cotyledon stage. The detection results were similar for similar types of crops. Thus, this method could be applied to crops with similar growth patterns. According to the results of 360 experiments that were conducted (five species of bean ${\times}$ six days ${\times}$ four speed levels ${\times}$ three repetitions), the location detection performance had an accuracy of 36.9%, and the range of location errors was 0-4.9 cm (RMSE = 3.1 cm). During a period of 3-5 days after the cotyledon stage, the location detection performance had an accuracy of 59% (RMSE = 3.9 cm). Conclusions: In the present study, to fundamentally solve the problem of damage to beans from birds in the early stage after seeding, a working method was proposed in which punching is carried out after seeding, thereby breaking away from the existing method in which seeding is carried out after punching. Methods for the accurate detection of soybean growing locations were studied to allow punching to promote the continuous growth of soybeans that had reached the cotyledon stage. Through experiments using multiple IR sensors and a sliding mechanical device, it was found that the locations of the crop could be partially identified 3-5 days after reaching the cotyledon stage regardless of the kind of pulse crop. It can be concluded that additional studies of robust detection methods considering environmental factors and factors for crop growth are necessary.

Three-dimensional human activity recognition by forming a movement polygon using posture skeletal data from depth sensor

  • Vishwakarma, Dinesh Kumar;Jain, Konark
    • ETRI Journal
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    • v.44 no.2
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    • pp.286-299
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    • 2022
  • Human activity recognition in real time is a challenging task. Recently, a plethora of studies has been proposed using deep learning architectures. The implementation of these architectures requires the high computing power of the machine and a massive database. However, handcrafted features-based machine learning models need less computing power and very accurate where features are effectively extracted. In this study, we propose a handcrafted model based on three-dimensional sequential skeleton data. The human body skeleton movement over a frame is computed through joint positions in a frame. The joints of these skeletal frames are projected into two-dimensional space, forming a "movement polygon." These polygons are further transformed into a one-dimensional space by computing amplitudes at different angles from the centroid of polygons. The feature vector is formed by the sampling of these amplitudes at different angles. The performance of the algorithm is evaluated using a support vector machine on four public datasets: MSR Action3D, Berkeley MHAD, TST Fall Detection, and NTU-RGB+D, and the highest accuracies achieved on these datasets are 94.13%, 93.34%, 95.7%, and 86.8%, respectively. These accuracies are compared with similar state-of-the-art and show superior performance.

3D Conversion of 2D Video Encoded by H.264

  • Hong, Ho-Ki;Ko, Min-Soo;Seo, Young-Ho;Kim, Dong-Wook;Yoo, Ji-Sang
    • Journal of Electrical Engineering and Technology
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    • v.7 no.6
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    • pp.990-1000
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    • 2012
  • In this paper, we propose an algorithm that creates three-dimensional (3D) stereoscopic video from two-dimensional (2D) video encoded by H.264 instead of using two cameras conventionally. Very accurate motion vectors are available in H.264 bit streams because of the availability of a variety of block sizes. 2D/3D conversion algorithm proposed in this paper can create left and right images by using extracted motion information. Image type of a given image is first determined from the extracted motion information and each image type gives a different conversion algorithm. The cut detection has also been performed in order to prevent overlapping of two totally different scenes for left and right images. We show an improved performance of the proposed algorithm through experimental results.

Analytic simulator and image generator of multiple-scattering Compton camera for prompt gamma ray imaging

  • Kim, Soo Mee
    • Biomedical Engineering Letters
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    • v.8 no.4
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    • pp.383-392
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    • 2018
  • For prompt gamma ray imaging for biomedical applications and environmental radiation monitoring, we propose herein a multiple-scattering Compton camera (MSCC). MSCC consists of three or more semiconductor layers with good energy resolution, and has potential for simultaneous detection and differentiation of multiple radio-isotopes based on the measured energies, as well as three-dimensional (3D) imaging of the radio-isotope distribution. In this study, we developed an analytic simulator and a 3D image generator for a MSCC, including the physical models of the radiation source emission and detection processes that can be utilized for geometry and performance prediction prior to the construction of a real system. The analytic simulator for a MSCC records coincidence detections of successive interactions in multiple detector layers. In the successive interaction processes, the emission direction of the incident gamma ray, the scattering angle, and the changed traveling path after the Compton scattering interaction in each detector, were determined by a conical surface uniform random number generator (RNG), and by a Klein-Nishina RNG. The 3D image generator has two functions: the recovery of the initial source energy spectrum and the 3D spatial distribution of the source. We evaluated the analytic simulator and image generator with two different energetic point radiation sources (Cs-137 and Co-60) and with an MSCC comprising three detector layers. The recovered initial energies of the incident radiations were well differentiated from the generated MSCC events. Correspondingly, we could obtain a multi-tracer image that combined the two differentiated images. The developed analytic simulator in this study emulated the randomness of the detection process of a multiple-scattering Compton camera, including the inherent degradation factors of the detectors, such as the limited spatial and energy resolutions. The Doppler-broadening effect owing to the momentum distribution of electrons in Compton scattering was not considered in the detection process because most interested isotopes for biomedical and environmental applications have high energies that are less sensitive to Doppler broadening. The analytic simulator and image generator for MSCC can be utilized to determine the optimal geometrical parameters, such as the distances between detectors and detector size, thus affecting the imaging performance of the Compton camera prior to the development of a real system.

Image sensed process controller for automatic paint spray systems (영상 검출에 의한 자동도포장치의 프로세서제어기)

  • 이상훈;유희삼;강준길
    • 제어로봇시스템학회:학술대회논문집
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    • 1986.10a
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    • pp.188-190
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    • 1986
  • In this paper, we describe an optical detection at the front and design an on-off control system of spray gun for economical paint spray when painted on hanger any things that it have arbitrary two-dimensional image. The objectives of this paper that, as changing of software, find useful logic variation of spray, and are to enhance of environments for workman and to decrease economical loss of painting.

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A Study on the Coordinate Transformation by Using the Analog Signal Processing (아날로그 신호처리에 의한 좌표변환에 관한 연구)

  • Che, Woo-Seong;Park, Seo-Wook;Oh, Jun-Ho
    • Journal of the Korean Society for Precision Engineering
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    • v.6 no.4
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    • pp.119-125
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    • 1989
  • This paper presents a method of analog signal processing for a coordinate transformation. Through the proposed method, two-dimensional position information obtanided from any type of null-detector can be transformed into the information with repect to world coordinate system. In order to implement the method, a null- detection device which consists of four optical proximity sensor is developed. Through the experiments for performance evaluation, the effectiveness of the proposed method has been demonstrated.

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Image Processing Algorithm for Robotic Plug-Seedling (플러그 묘 이식용 로봇의 영상 처리 알고리즘)

  • 김철수;김만수;김기대
    • Journal of Biosystems Engineering
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    • v.24 no.1
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    • pp.51-58
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    • 1999
  • A color image processing algorithm was developed to assist the robotic plug-seedling transplanter. The algorithm was designed to identify and locate empty cells in the seedling tray. The image of pepper seedling tray was segmented into regions of plant, frame and soil using thresholding technique which utilized HSI or RGB color characteristics of each region. The detection algorithm was able to successfully identify empty cells and locate their two-dimensional location. The overall success rate of the algorithm was about 88%.

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Context Dependent Feature Point Detection in Digital Curves (Context를 고려한 디지털 곡선의 특징점 검출)

  • 유병민;김문현;원동호
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.4
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    • pp.590-597
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    • 1990
  • To represent shape characteristics of digital closed curve, many algorithms, mainly based on local properties, have been proposed. In this paper, we propose a new algorithm for detecting local curvature maxima which reflects context, i.e., structural or surrounding regional characteristics. The algorithm does not require the value of k as an input parameter which is the major problem in k-curvature method in digital curve, but calculates it at each point depening on the context. The algorithm has been applied to two dimensional image boundaries. The efficiency of the algorithm is addressed by comparing the result of existing contest dependent algorithm.

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